Liyao Ma

Orcid: 0000-0002-4661-1347

According to our database1, Liyao Ma authored at least 28 papers between 2013 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Bibliography

2024
An OWA-Based Distance Measure for Ordered Frames of Discernment.
Proceedings of the Belief Functions: Theory and Applications, 2024

2023
Teaching Exploration on Calculation Method Under the Background of Emerging Engineering Education.
Proceedings of the Multimedia Technology and Enhanced Learning, 2023

Gaussian Mass Function Based Multiple Model Fusion for Apple Classification.
Proceedings of the Multimedia Technology and Enhanced Learning, 2023

2022
Apple grading method based on neural network with ordered partitions and evidential ensemble learning.
CAAI Trans. Intell. Technol., December, 2022

Belief Entropy Tree and Random Forest: Learning from Data with Continuous Attributes and Evidential Labels.
Entropy, 2022

Ordinal Classification Using Single-Model Evidential Extreme Learning Machine.
Proceedings of the Belief Functions: Theory and Applications, 2022

2021
A Robust Data-Driven Method for Multiseasonality and Heteroscedasticity in Time Series Preprocessing.
Wirel. Commun. Mob. Comput., 2021

Neural network assisted Kalman filter for INS/UWB integrated seamless quadrotor localization.
PeerJ Comput. Sci., 2021

Partial classification in the belief function framework.
Knowl. Based Syst., 2021

Research on the Application of Augmented Reality Technology in the Transformation and Development of Cultural and Creative Industries.
EAI Endorsed Trans. Creative Technol., 2021

Apple Classification Based on Information Fusion of Internal and External Qualities.
Proceedings of the Multimedia Technology and Enhanced Learning, 2021

LS-SVM/Federated EKF Based on the Distributed INS/UWB Integrated 2D Localization.
Proceedings of the Multimedia Technology and Enhanced Learning, 2021

Matrix Profile Evolution: An Initial Overview.
Proceedings of the Multimedia Technology and Enhanced Learning, 2021

A Classification Tree Method Based on Belief Entropy for Evidential Data.
Proceedings of the Belief Functions: Theory and Applications, 2021

2020
Prediction Analysis of Soluble Solids Content in Apples Based on Wavelet Packet Analysis and BP Neural Network.
Proceedings of the Multimedia Technology and Enhanced Learning, 2020

2019
Making Set-Valued Predictions in Evidential Classification: A Comparison of Different Approaches.
Proceedings of the International Symposium on Imprecise Probabilities: Theories and Applications, 2019

Social Media Competition for User Satisfaction: A Niche Analysis of Facebook, Instagram, YouTube, Pinterest, and Twitter.
Proceedings of the Advances in Artificial Intelligence, Software and Systems Engineering, 2019

2018
Operator-Based Control System Analysis and Design for Nonlinear System with Input and Output Constraints.
J. Robotics Mechatronics, 2018

Anomaly-Aware Traffic Prediction Based on Automated Conditional Information Fusion.
Proceedings of the 21st International Conference on Information Fusion, 2018

Training Instance Random Sampling Based Evidential Classification Forest Algorithms.
Proceedings of the 21st International Conference on Information Fusion, 2018

2017
A modified belief rule based model for uncertain nonlinear systems identification.
J. Intell. Fuzzy Syst., 2017

Learning decision forest from evidential data: The random training set sampling approach.
Proceedings of the 4th International Conference on Systems and Informatics, 2017

Bagging likelihood-based belief decision trees.
Proceedings of the 20th International Conference on Information Fusion, 2017

2016
Online active learning of decision trees with evidential data.
Pattern Recognit., 2016

2015
Evidential likelihood flatness as a way tomeasure data quality: the multinomial case.
Proceedings of the 2015 Conference of the International Fuzzy Systems Association and the European Society for Fuzzy Logic and Technology (IFSA-EUSFLAT-15), 2015

2014
When and to what extent should two belief functions be discounted?
Proceedings of the 17th International Conference on Information Fusion, 2014

Some Notes on Canonical Decomposition and Separability of a Belief Function.
Proceedings of the Belief Functions: Theory and Applications, 2014

2013
A dissimilarity measure based on singular value and its application in incremental discounting.
Proceedings of the 16th International Conference on Information Fusion, 2013


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